jmo [he/him, comrade/them]

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Joined 2 months ago
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Cake day: March 16th, 2026

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  • Ok, the numbers and spend question led me down a really interesting rabbit hole and I wanted to share a little bit of what I learned. TL;DR AI data center spend, in absolute and relative terms, is really high. Please take all my statements with a heavy dose of salt as I’m not an economist or professional researcher.

    It’s probably less than railroads ~6% of GDP and probably more than telco spend leading up to the dotcom bubble ~1.5% of GDP. It’s reasonable to guess that is represents, or will by the end of 2026, ~ 2.2% of US GDP. Like the dotcom bubble it’s largely funded by private capital. Unlike the dotcom bubble it’s much more reliant on debt, specifically private credit debt, we’ll get back to why that might matter later. Where things get interesting is in the durable nature of the utility value of the goods produced by the investment. Railroad capital mostly has a 100+ year utility value, tracks can be used for a long time with some regular maintenance. Fiber has a 15+ year, probably a lot longer, utility value and again a lot of the associated infrastructure stays useful for a long time with maintenance. Data center infrastructure and GPUs are not so lucky. The people spending the money say the GPUs are good for 5 years, they probably have a 1-3 year usable lifespan. Data center infrastructure itself has a much longer useful lifespan but those buildings aren’t exactly general purpose, if AI is a bust you’ll need to have a new use for all that space. The so what of all that is this is looking even less rational and useful than the dotcom era infrastructure investment boom.

    On the debt financing thing I talked about getting back to I’d suggest you take a look at this article that has the heterodox economist Michal Hudson talking about why he thinks the west is in for a really bad ride if AI + private credit + energy crisis all come together for a lemon party type situation.


  • Yes! I was just having this discussion last night. We have another 2.5 trillion in capex, the money corporations allocate to investing in their infrastructure, committed to AI datacenter buildout this year. That’s A LOT of money. It’s not being spent on bridges, roads, hospitals, schools, etc. It’s being spent on specialized data centers intended to house massive GPU farms to run and train the latest and greatest AI models.

    AFAICT this only pays off they manage to actually beat the theoretically limitations of these LLMs and make a machine god. The so what of all that is we have A LOT of capital chasing, what is probably, a fantasy. As it does so it isn’t creating a useful stay behind asset. AI datacenters aren’t general purpose and can’t be easily reused. Add to that the fact that the GPUs don’t actually have a very long productive life and you start to see problems compound.

    One important methodological note here: Zitron’s numbers on Capex are WAY better than mine. I did some digging into that 2.5 trillion number while writing this comment and found out that was based on a single source, Gartner, which has an incentive to pump up the numbers.